Feed forward Artificial Neural Network model to predict the average summer-monsoon rainfall in India

In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial Neural Network model. In formulating the ANN — based predictive model, three-layer network has been constructed with sigmoid non-linearity. The monthly summer monsoon rainfall totals, tropical rainfall indices and sea surface temperature anomalies have been considered as predictors while generating the input matrix for the ANN. The data pertaining to the years 1950–1995 have been explored to develop the predictive model. Finally, the prediction performance of neural net has been compared with persistence forecast and Multiple Linear Regression forecast and the supremacy of the ANN has been established over the other processes.     

Prediction of Chinese Loess Plateau summer rainfall using Pacific Ocean spring sea surface temperature

The Loess Plateau in China constitutes an important source area for both water and sediments to the Yellow River. Thus, improved prediction techniques of rainfall may lead to better estimation of discharge and sediment content for the Yellow River. Consequently, the objective of this study was to establish better links between rainfall of the Loess Plateau in China and sea surface temperature (SST) in the Pacific Ocean. Results showed that there is a strong lagged correlation between and SST and rainfall. The SST for Micronesia and areas south of the Aleutian Islands showed significant correlations (s.f. < 0·001; 99·9%) with rainfall over the dryer region of the Loess Plateau for a lag of 4 to 6 months. The SST over the equator on the east Pacific Ocean also showed significant negative correlation with rainfall. Low and middle latitude areas (S10–20° and around 30° ) of the south‐east Pacific Ocean displayed significant positive and negative correlation with rainfall on the semiarid Loess Plateau. The differenced SST values (positive SST minus negative SST) increased these correlations with rainfall. An artificial neural network (ANN) model was used to predict summer rainfall from the differenced SST during the spring period. The correlation between predicted and observed monthly rainfall was in general larger than 0·7. This indicates that major annual rainfall (during summer season) can be predicted with good accuracy using the suggested approach. Copyright © 2008 John Wiley & Sons, Ltd.     

Decadal scale variability of sea surface temperature in the Mediterranean Sea in relation to atmospheric variability

Twenty-four years of AVHRR-derived sea surface temperature (SST) data (1985–2008) and 35 years of NOCS (V.2) in situ-based SST data (1973–2008) were used to investigate the decadal scale variability of this parameter in the Mediterranean Sea in relation to local air–sea interaction and large-scale atmospheric variability. Satellite and in situ-derived data indicate a strong eastward increasing sea surface warming trend from the early 1990s onwards. The satellite-derived mean annual warming rate is about 0.037°C year^–1 for the whole basin, about 0.026°C year^–1 for the western sub-basin and about 0.042°C year^–1 for the eastern sub-basin over 1985–2008. NOCS-derived data indicate similar variability but with lower warming trends for both sub-basins over the same period. The long-term Mediterranean SST spatiotemporal variability is mainly associated with horizontal heat advection variations and an increasing warming of the Atlantic inflow. Analysis of SST and net heat flux inter-annual variations indicates a negative correlation, with the long-term SST increase, driving a net air–sea heat flux decrease in the Mediterranean Sea through a large increase in the latent heat loss. Empirical orthogonal function (EOF) analysis of the monthly average anomaly satellite-derived time series showed that the first EOF mode is associated with a long-term warming trend throughout the whole Mediterranean surface and it is highly correlated with both the Eastern Atlantic (EA) pattern and the Atlantic Multidecadal Oscillation (AMO) index. On the other hand, SST basin-average yearly anomaly and NAO variations show low and not statistically significant correlations of opposite sign for the eastern (negative correlation) and western (positive correlation) sub-basins. However, there seems to be a link between NAO and SST decadal-scale variations that is particularly evidenced in the second EOF mode of SST anomalies. NOCS SST time series show a significant SST rise in the western basin from 1973 to the late 1980s following a large warming of the inflowing surface Atlantic waters and a long-term increase of the NAO index, whereas SST slowly increased in the eastern basin. In the early 1990s, there is an abrupt change from a very high positive to a low NAO phase which coincides with a large change in the SST spatiotemporal variability pattern. This pronounced variability shift is followed by an acceleration of the warming rate in the Mediterranean Sea and a change in the direction (from westward to eastward) of its spatial increasing tendency.     

Role of Ocean in the Variability of Indian Summer Monsoon Rainfall

Asian summer monsoon sets in over India after the Intertropical Convergence Zone moves across the equator to the northern hemisphere over the Indian Ocean. Sea surface temperature (SST) anomalies on either side of the equator in Indian and Pacific oceans are found related to the date of monsoon onset over Kerala (India). Droughts in the June to September monsoon rainfall of India are followed by warm SST anomalies over tropical Indian Ocean and cold SST anomalies over west Pacific Ocean. These anomalies persist till the following monsoon which gives normal or excess rainfall (tropospheric biennial oscillation). Thus, we do not get in India many successive drought years as in sub-Saharan Africa, thanks to the ocean. Monsoon rainfall of India has a decadal variability in the form of 30-year epochs of frequent (infrequent) drought monsoons occurring alternately. Decadal oscillations of monsoon rainfall and the well-known decadal oscillation in SST of the Atlantic Ocean (also of the Pacific Ocean) are found to run parallel with about the same period close to 60 years and the same phase. In the active–break cycle of the Asian summer monsoon, the ocean and the atmosphere are found to interact on the time scale of 30–60 days. Net heat flux at the ocean surface, monsoon low-level jetstream (LLJ) and the seasonally persisting shallow mixed layer of the ocean north of the LLJ axis play important roles in this interaction. In an El Niño year, the LLJ extends eastwards up to the date line creating an area of shallow ocean mixed layer there, which is hypothesised to lengthen the active–break (AB) cycle typically from 1 month in a La Niña to 2 months in an El Niño year. Indian monsoon droughts are known to be associated with El Niños, and long break monsoon spells are found to be a major cause of monsoon droughts. In the global warming scenario, the observed rapid warming of the equatorial Indian ocean SST has caused the weakening of both the monsoon Hadley circulation and the monsoon LLJ which has been related to the observed rapid decreasing trend in the seasonal number of monsoon depressions.     

Indian summer monsoon and El Nino

The associations between strong to moderate El Nino events and the all-India and subdivisional summer monsoon rainfall is examined for the period 1871 to 1978. The significance of the association is assessed by applying the Chi-square test to the contingency table. The analysis indicates that during 22 El Nino years the Indian monsoon rainfall was mostly below normal over most parts of the country. However, the association between El Nino and deficient rainfall or drought is statistically significant over the subdivisions west of longitude 80°E and north of 12°N. During the five strong El Nino years—1877, 1899, 1911, 1918, and 1972—many areas of India suffered large rainfall deficiencies and severe droughts. There are four moderate El Nino years—1887, 1914, 1953, and 1976—when the suffering was marginal. The relationship between El Nino and the Indian monsoon rainfall is expected to be useful in forecasting large-scale anomalies in the monsoon over India.     

An anomalous cooling event observed in the Bay of Bengal during June 2009

Sea surface temperature (SST) variability over the Bay of Bengal (BoB) has the potential to trigger deep moist convection thereby affecting the active-break cycle of the monsoons. Normally, during the summer monsoon season, SST over the BoB is observed to be greater than 28°C which is a pre-requisite for convection. During June 2009, satellite observations revealed an anomalous basin-wide cooling and the month is noted for reduced rainfall over the Indian subcontinent. In this study, we analyze the likely mechanisms of this cooling event using both satellite and moored buoy observations. Observations showed deepened mixed layer, stronger surface currents, and enhanced heat loss at the surface in the BoB. Mixed layer heat balance analysis is carried out to resolve the relative importance of various processes involved. We show that the cooling event is primarily induced by the heat losses at the surface resulting from the strong wind anomalies, and advection and vertical entrainment playing secondary roles.     

Sea level changes induced by local winds on the west coast of India

The contribution of atmospheric pressure and local wind to sea level variability at Goa (West coast of India) for the period 2007–2008 is investigated. Sea level data from a tide gauge are compared with measured local surface meteorological as well as oceanographic data. Multilinear regression analysis is used to resolve the dependence of sea level on various forcing parameters. The multilinear regression analysis performed over approx. 2-year data shows that the local surface meteorological data and water temperature account for the sea level variability only up to 6%. The accounted sea level variability increases to 25%, when the local wind and the surface currents obtained from satellite altimetry in the near vicinity of the study area are incorporated in the regression analysis. The contribution of local wind increases substantially when the regression is performed over a 2-month duration, and it is variable within the year. During the summer monsoon season (May–September), the sea level variability attributable to wind is up to 47% and 75%, respectively, for 2007 and 2008; however, it reduces to <20% during the winter monsoon (November–February) season. A significant part of the variability observed in sea level remains unaccounted for and is attributed to remote forcing.     

Hydroclimatic teleconnection between global sea surface temperature and rainfall over India at subdivisional monthly scale

It is well established that sea surface temperature (SST) plays a significant role in the hydrologic cycle in which precipitation is the most important part. In this study, the influence of SST on Indian subdivisional monthly rainfall is investigated. Both spatial and temporal influences are investigated. The most influencing regions of sea surface are identified for different subdivisions and for different overlapping seasons in the year. The relative importance of SST, land surface temperature (LST) and ocean–land temperature contrast (OLTC) and their variation from subdivision to subdivision and from season to season are also studied. It is observed that LST does not show much similarity with rainfall series, but, in general, OLTC shows relatively higher influence in the pre‐monsoon and early monsoon periods, whereas SST plays a more important role in late‐ and post‐monsoon periods. The influence of OLTC is seen to be mostly confined to the Indian Ocean region, whereas the effect of SST indicates the climatic teleconnection between Indian regional rainfall and climate indices in Pacific and Atlantic Oceans. Copyright © 2006 John Wiley & Sons, Ltd.     

南海夏季风爆发与南大洋海温变化之间的联系

利用1979-2009年NCEP第二套大气再分析资料和ERSST海温资料,分析南海夏季风爆发时间的年际和年代际变化特征,考察南海夏季风爆发早晚与南大洋海温之间的联系.主要结果为:(1)南海夏季风爆发时间年际和年代际变化明显,1979-1993年与1994-2009年前后两个阶段爆发时间存在阶段性突变;(2)南海夏季风爆发时间与前期冬季(12-1月)印度洋-南大洋(0-80°E,75°S-50°S)海温、春季(2-3月)太平洋-南大洋(170°E -80°W,75°S-50°S)海温都存在正相关关系,当前期冬、春季南大洋海温偏低(高)时,南海夏季风爆发偏早(晚).南大洋海温信号,无论是年际还是年代际变化,都对南海夏季风爆发具有一定的预测指示作用;(3)南大洋海温异常通过海气相互作用和大气遥相关影响南海夏季风爆发的迟早.当南大洋海温异常偏低(偏高)时,冬季南极涛动偏强(偏弱),同时通过遥相关作用使热带印度洋-西太平洋地区位势高度偏低(偏高)、纬向风加强(减弱),热带大气这种环流异常一直维持到春季4、5月份,位势高度和纬向风异常范围逐步向北扩展并伴随索马里越赤道气流的加强(减弱),从而为南海夏季风爆发偏早(偏晚)提供有利的环流条件.初步分析认为,热带大气环流对南大洋海气相互作用的遥响应与半球际大气质量重新分布引起的南北涛动有关.     

赤道MJO活动对南海夏季风爆发的影响

利用1979—2013年NCEP/DOE再分析资料的大气多要素日平均资料、美国NOAA日平均向外长波辐射资料和ERSST月平均海温资料,分析赤道大气季节内振荡(简称MJO)活动对南海夏季风爆发的影响及其与热带海温信号等的协同作用.结果表明,赤道MJO活动与南海夏季风爆发密切联系,MJO的湿位相(即对流活跃位相)处于西太平洋位相时,有利于南海夏季风爆发,而MJO湿位相处于印度洋位相时,则不利于南海夏季风爆发.赤道MJO活动影响南海夏季风爆发的物理过程主要是大气对热源响应的结果,当MJO湿位相处于西太平洋位相时,一方面热带西太平洋对流加强使潜热释放增加,导致处于热源西北侧的南海—西北太平洋地区对流层低层由于Rossby响应产生气旋性环流异常,气旋性环流异常则有利于西太平洋副热带高压的东退,另一方面菲律宾附近热源促进对流层高层南亚高压在中南半岛和南海北部的建立,使南海地区高层为偏东风,从而有利于南海夏季风建立;当湿位相MJO处于印度洋位相时,热带西太平洋对流减弱转为大气冷源,情况基本相反,不利于南海夏季风建立.MJO活动、孟加拉湾气旋性环流与年际尺度海温变化协同作用,共同对南海夏季风爆发迟早产生影响,近35年南海夏季风爆发时间与海温信号不一致的年份,基本上是由于季节转换期间的MJO活动特征及孟加拉湾气旋性环流是否形成而造成,因此三者综合考虑对于提高季风爆发时间预测水平具有重要意义.     

On the Predictability of Northeast Monsoon Rainfall over South Peninsular India in General Circulation Models

In this study the predictability of northeast monsoon (Oct–Nov–Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982–2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model.     

Simulation of Monsoon Disturbances in a GCM

--A large part of the rainfall over India during the summer monsoon season (June-September) is contributed by synoptic scale disturbances such as monsoon depressions. To study the evolution of such disturbances in Atmospheric General Circulation Models (AGCM), the Hadley Centre AGCM (HadAM2b) has been integrated for 15 summer monsoons (1979-1993) and the output was examined for the presence of synoptic scale disturbances such as monsoon depressions, low pressure areas, land lows and land depressions over the Indian summer monsoon region. The atmospheric initial condition for each of these integrations was of 23rd May and observed Sea Surface Temperatures (SST) were described as a boundary condition.¶Although the horizontal resolution of the AGCM used in this study is only 2.5° 2 3.75° lat. long., the model is able to simulate a few monsoon disturbances. The important features of these simulated disturbances are presented. The features of the simulated disturbances are realistic. The morphologies of a well simulated monsoon depression and a simulated low pressure area are presented as examples. The frequency of the simulated monsoon depressions is less than the climatological frequency of the depressions during all four monsoon months.     

Comparative influence of land and sea surfaces on the Sahelian drought: a numerical study

The aim of this work is to compare the relative impact of land and sea surface anomalies on Sahel rainfall and to describe the associated anomalies in the atmospheric general circulation. This sensitivity study was done with the Météo-France climate model: ARPEGE. The sensitivity to land surface conditions consists of changes in the management of water and heat exchanges by vegetation cover and bare soil. The sensitivity to ocean surfaces consists in forcing the lower boundary of the model with worldwide composite sea surface temperature (SST) anomalies obtained from the difference between 4 dry Sahel years and 4 wet Sahel years observed since 1970. For each case, the spatiotemporal variability of the simulated rainfall anomaly and changes in the modelled tropical easterly jet (TEJ) and African easterly jet (AEJ) are discussed. The global changes in land surface evaporation have caused a rainfall deficit over the Sahel and over the Guinea Coast. No significant changes in the simulated TEJ and an enhancement of the AEJ are found; at the surface, the energy budget and the hydrological cycle are substantially modified. On the other hand, SST anomalies induce a negative rainfall anomaly over the Sahel and a positive rainfall anomaly to the south of this area. The rainfall deficit due to those anomalies is consistent with previous diagnostic and sensitivity studies. The TEJ is weaker and the AEJ is stronger than in the reference. The composite impact of SST and land surfaces anomalies is also analyzed: the simulated rainfall anomaly is similar to the observed mean African drought patterns. This work suggests that large-scale variations of surface conditions may have a substantial influence on Sahel rainfall and shows the importance of land surface parameterization in climate change modelling. In addition, it points out the interest in accurately considering the land and sea surfaces conditions in sensitivity studies on Sahel rainfall.     

A high-resolution satellite-derived sea surface temperature climatology for the western North Atlantic Ocean

Long-term and high-resolution (∼1.2 km) satellite-derived sea surface temperature (SST) fields of a monthly mean time series for the 1985–1999 period, and a daily climatology have been calculated for the North West Atlantic Ocean. The SST fields extend from 78°W to 41°W in longitude, and 30°N to 56°N in latitude, encompassing the region off Cape Hatteras, North Carolina, to the southern Labrador Sea. The monthly mean time series, consists of 180 cloud-masked monthly mean SST fields, derived from a full-resolution NOAA/NASA Pathfinder SST data set for the 1985–1999 period. The satellite-derived monthly mean SST fields, as compared with in situ monthly mean near-surface ocean temperatures from buoys located in the western North Atlantic, yield an overall RMS difference of 1.15 °C. The daily climatology, which consists of 365 fields, was derived by applying a least-squares harmonic regression technique on the monthly mean SST time series for the full study period. The monthly mean and daily climatological SST fields will be useful for studying inter-annual variability related to climate variability of SST over the study domain.     

Quasi-periodic fluctuations in the Greenland–Iceland–Norwegian Seas region in a coupled climate model

We report an analysis of the mechanisms responsible for interannual variability in the Greenland–Iceland–Norwegian (GIN) Seas in a control integration of the HadCM3 coupled climate model. Interannual variability in sea surface temperature (SST) and sea surface salinity (SSS) is dominated by a quasi-periodic ∼7-year signal. Analyses show that the mechanism involves a competition between convection and advection. Advection carries cold, fresh, Arctic water over warm, salty, Atlantic water, while convection periodically mixes these two water masses vertically, raising SST. Convection is able to raise SST because of the presence of a subsurface temperature maximum. The GIN Seas convection in HadCM3 is forced by wind stress anomalies related to the North Atlantic Oscillation (NAO). The consequent SST anomalies feedback positively to force the atmosphere, resulting in a weak spectral peak (at ∼7 years) in GIN Seas sea level pressure. Although there is no evidence of a similar oscillation in reality, key aspects of the simulated mechanism may be relevant to understanding variability in the real GIN Seas. In particular, the potential for increases in convection to raise SST offers a possible new explanation for increases in SST that occurred between the 1960s and the late 1980s/early 1990s. These SST increases may have contributed to the observed sea-ice retreat. In addition, a positive feedback between GIN Seas SST and the atmosphere could contribute to the persistence of the NAO, potentially helping to explain its red spectrum or recent northeastward shift.

Variability of Convective Activity over the North Indian Ocean and its Associations with Monsoon Rainfall over India

The present study is an attempt to examine the variability of convective activity over the north Indian Ocean (Bay of Bengal and Arabian Sea) on interannual and longer time scale and its association with the rainfall activity over the four different homogeneous regions of India (viz., northeast India, northwest India, central India and south peninsular India) during the monsoon season from June to September (JJAS) for the 26 year period (1979 to 2004). The monthly mean Outgoing Long-wave Radiation (OLR) data obtained from National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft are used in this study and the 26-year period has been divided into two periods of 13 years each with period-i from 1979 to 1991 and period -ii from 1992 to 2004. It is ascertained that the convective activity increases over the Arabian Sea and the Bay of Bengal in the recent period (period -ii; 1992 to 2004) compared to that of the former period (period -i; 1979 to 1991) during JJAS and is associated with a significantly increasing trend (at 95% level) of convective activity over the north Bay of Bengal (NBAY). On a monthly scale, July and August also show increase in convective activity over the Arabian Sea and the Bay of Bengal during the recent period and this is associated with slight changes in the monsoon activity cycle over India. The increase in convective activity particularly over the Arabian Sea during the recent period of June is basically associated with about three days early onset of the monsoon over Delhi and relatively faster progress of the monsoon northward from the southern tip of India. Over the homogeneous regions of India the correlation coefficient (CC) of OLR anomalies over the south Arabian Sea (SARA) is highly significant with the rainfall over central India, south peninsular India and northwest India, and for the north Arabian Sea (NARA), it is significant with northwest India rainfall and south peninsular rainfall. Similarly, the OLR anomalies over the south Bay of Bengal (SBAY) have significant CC with northwest India and south peninsular rainfall, whereas the most active convective region of the NBAY is not significantly correlated with rainfall over India. It is also found that the region over northeastern parts of India and its surroundings has a negative correlation with the OLR anomalies over the NARA and is associated with an anomalous sinking (rising) motion over the northeastern parts of India during the years of increase (decrease) of convective activity over the NARA.     

Trends in rainfall and temperature in the Peruvian Amazon–Andes basin over the last 40 years (1965–2007)

The hydroclimatology of the Peruvian Amazon–Andes basin (PAB) which surface corresponding to 7% of the Amazon basin is still poorly documented. We propose here an extended and original analysis of the temporal evolution of monthly rainfall, mean temperature (T_mean), maximum temperature (T_max) and minimum temperature (T_min) time series over two PABs (Huallaga and Ucayali) over the last 40 years. This analysis is based on a new and more complete database that includes 77 weather stations over the 1965–2007 period, and we focus our attention on both annual and seasonal meteorological time series. A positive significant trend in mean temperature of 0.09 °C per decade is detected over the region with similar values in the Andes and rainforest when considering average data. However, a high percentage of stations with significant T_mean positive trends are located over the Andes region. Finally, changes in the mean values occurred earlier in T_max (during the 1970s) than in T_min (during the 1980s). In the PAB, there is neither trend nor mean change in rainfall during the 1965–2007 period. However, annual, summer and autumn rainfall in the southern Andes presents an important interannual variability that is associated with the sea surface temperature in the tropical Atlantic Ocean while there are limited relationships between rainfall and El Niño‐Southern Oscillation (ENSO) events. On the contrary, the interannual temperature variability is mainly related to ENSO events. Copyright © 2012 John Wiley & Sons, Ltd.     

Monsoonal precipitation variation in the East Asia since A.D. 1840

Three tree-ring rainfall reconstructions from China and Korea are used in this paper to investigate the East Asian summer monsoon-related precipitation variation over the past 160 years. Statistically, there is no linear correlation on a year-by-year basis between Chinese and Korean monsoon rainfall, but region-wide synchronous variation on a decadal-scale was observed. More rainfall intervals were 1860–1890, 1910–1925, and 1940–1960, and dry or even drought periods were 1890–1910, 1925–1940, and 1960–present. Reconstructions also display that the East Asian summer monsoon precipitation suddenly changed from more into less around mid-1920. These tree-ring precipitation records were also confirmed by Chinese historical dryness/wetness index and Korean historical rain gauge data.     

Recent warming in the Yellow/East China Sea during winter and the associated atmospheric circulation

We examine characteristics in the variability of sea surface temperature (SST) in the Yellow/East China Sea during the boreal winter (December–January–February) for the period 1950–2008 in observations. It is found that the mean SST in the Yellow Sea/East China Sea gradually increases during recent decades. A warming trend of a basin scale SST is significant in most of the regions in the Yellow/East Sea, which is well explained by the variability of the first empirical orthogonal function SST mode. We suggest one candidate mechanism that the North Pacific oscillation (NPO)-like sea level pressure play an important role to warm the Yellow/East China Sea. Anomalous anticyclonic circulation, which is the southern lobe of NPO-like sea level pressure over the North Pacific, causes a weakening of northerly mean winds over the Yellow/East China Sea during winter. This contributes to increase in the SST in the Yellow/East China Sea through the changes in the latent heat and sensible heat fluxes.     

An Objective Approach for Prediction of Daily Summer Monsoon Rainfall over Orissa (India) due to Interaction of Mesoscale and Large-scale Synoptic Systems

Orissa State, a meteorological subdivision of India, lies on the east coast of India close to north Bay of Bengal and to the south of the normal position of the monsoon trough. The monsoon disturbances such as depressions and cyclonic storms mostly develop to the north of 15° N over the Bay of Bengal and move along the monsoon trough. As Orissa lies in the southwest sector of such disturbances, it experiences very heavy rainfall due to the interaction of these systems with mesoscale convection sometimes leading to flood. The orography due to the Eastern Ghat and other hill peaks in Orissa and environs play a significant role in this interaction. The objective of this study is to develop an objective statistical model to predict the occurrence and quantity of precipitation during the next 24 hours over specific locations of Orissa, due to monsoon disturbances over north Bay and adjoining west central Bay of Bengal based on observations to up 0300 UTC of the day. A probability of precipitation (PoP) model has been developed by applying forward stepwise regression with available surface and upper air meteorological parameters observed in and around Orissa in association with monsoon disturbances during the summer monsoon season (June-September). The PoP forecast has been converted into the deterministic occurrence/non-occurrence of precipitation forecast using the critical value of PoP. The parameters selected through stepwise regression have been considered to develop quantitative precipitation forecast (QPF) model using multiple discriminant analysis (MDA) for categorical prediction of precipitation in different ranges such as 0.1–10, 11–25, 26–50, 51–100 and >100 mm if the occurrence of precipitation is predicted by PoP model. All the above models have been developed based on data of summer monsoon seasons of 1980–1994, and data during 1995–1998 have been used for testing the skill of the models. Considering six representative stations for six homogeneous regions in Orissa, the PoP model performs very well with percentages of correct forecast for occurrence/non-occurrence of precipitation being about 96% and 88%, respectively for developmental and independent data. The skill of the QPF model, though relatively less, is reasonable for lower ranges of precipitation. The skill of the model is limited for higher ranges of precipitation. accepted September 2006